WO2021081911A1

WO2021081911A1 - Frequency analysis method and apparatus, and radar

Info

Publication number: WO2021081911A1
Application number: PCT/CN2019/114791
Authority: WO
Inventors: 王犇; 李德建
Original assignee: 华为技术有限公司
Priority date: 2019-10-31
Filing date: 2019-10-31
Publication date: 2021-05-06
Also published as: CN112585496B; CN112585496A

Abstract

A frequency analysis method and apparatus, and a radar, for use in improving robustness and accuracy of frequency analysis. An extended vector r is constructed, and frequency analysis and calculation are performed on the extended vector r. N vector elements in the extended vector r correspond to N manifold parameters. Each vector element in the N vector elements can indicate a cross covariance of at least one pair of receivers, and the manifold parameter corresponding to each vector element is used for indicating an ordered distance of a first receiver in each pair of receivers in the at least one pair of receivers corresponding to each vector element with respect to a second receiver. The extended vector r is obtained on the basis of second-order statistical characteristics of a received signal, and the amount of frequency analysis and calculation is increased by means of the extended vector r, so that the accuracy and robustness of a frequency analysis result are improved.

Description

Frequency analysis method, device and radar

Technical field

This application relates to the technical field of signal processing, and in particular to a frequency analysis method, device and radar.

Background technique

Frequency analysis is a common method for processing the received signals of the receiving array. For example, the receiving signal of the receiving array in the millimeter wave radar includes the echo signal. The millimeter wave radar can perform frequency analysis on the receiving signal of the receiving array to obtain the spatial spectrum of the echo signal, thereby estimating the direction of the echo signal.

At present, it is generally possible to perform frequency domain analysis on the received signal to obtain the spatial spectrum through fast Fourier transform (FFT) calculation or digital beam-forming (digital beam-forming, DBF) calculation. In the FFT calculation, the sampling data of the received signal of the receiving array at any sampling point can be obtained, and the fast Fourier transform is performed on the sampling data of the received signal at the sampling point to obtain the FFT spatial spectrum of the received signal. In the DBF calculation, the covariance matrix can be constructed according to the sampling data of the received signal at multiple sampling points, and the steering vector can be constructed according to the array structure of the receiving array, and then the DBF space spectrum can be calculated based on the covariance matrix and the steering vector.

However, the accuracy of the calculation result of the FFT calculation is more susceptible to the influence of the noise signal in the received signal, so that the robustness of the FFT calculation result is not high. However, DBF calculation requires more sampling points to obtain sufficient sampling data to obtain analysis results with higher accuracy. In the case of insufficient sampling data, the analysis results of the DBF algorithm are often not accurate enough.

In summary, the accuracy and robustness of the analysis results of the current frequency analysis methods need to be further improved.

Summary of the invention

In view of this, the present application provides a frequency analysis method, device, and radar for performing frequency analysis on the received signal of the receiving array, which is beneficial to improve the accuracy and robustness of the frequency analysis result.

In the first aspect, an embodiment of the present application provides a frequency analysis method, which can be used to analyze signals received by M receivers, where the M receivers are linearly arranged to form a receiving array, and M is greater than 1. Integer. The frequency analysis method provided by the embodiment of the present application mainly includes: constructing an expansion vector r including N vector elements, and performing frequency analysis and calculation on the expansion vector r according to the N flow pattern parameters of the receiving array.

In the embodiment of the present application, the N vector elements in the extension vector r correspond to the N flow type parameters. Among them, the N flow pattern parameters are related to the arrangement structure of the receiving array, and each flow pattern parameter can be understood as the orderly distance of the first receiver relative to the second receiver in a pair of receivers. In the embodiment of the present application, each of the N vector elements can indicate the mutual covariance of at least a pair of receivers, and the flow parameter corresponding to each vector element is used to indicate at least a pair of receivers corresponding to each vector element , The ordered distance of the first receiver relative to the second receiver in each pair of receivers.

In the embodiment of the present application, among the N vector elements of the extension vector r, each vector element may indicate the cross-covariance of at least a pair of receivers, where the cross-covariance is a second-order statistic. That is to say, the extension vector r in the embodiment of the present application is constructed according to the second-order statistical characteristics of the received signal of the receiving array. Compared with directly using sampled data for frequency analysis calculations (such as traditional FFT calculations), using the second-order statistical characteristics of the received signal to construct the expansion vector r is beneficial to improve the robustness of the frequency analysis results. Specifically, the sampling data is directly used for frequency analysis and calculation. Because the randomness of the noise signal in the received signal is strong, the frequency analysis result is affected by the randomness of the noise signal, so that the accuracy of the frequency analysis result will vary with the change of the noise signal. Fluctuations, so the robustness of the frequency analysis results is not strong. The second-order statistics are used to construct the expansion vector r. Since the second-order statistics can reduce the influence of the fluctuation of the noise signal on the frequency analysis result, the frequency analysis calculation is performed on the expansion vector r provided in the embodiment of the present application, even if the noise signal changes , The frequency analysis results can also maintain high stability, that is, robustness.

At the same time, the expansion vector r constructed in the embodiment of the application conforms to the correlation between the second-order statistical characteristics of the received signal and the structure of the receiving array. Therefore, the data added by the expansion vector r in the embodiment of the application is valid data. The embodiment is also beneficial to increase the number of frequency analysis calculations, that is, to increase the data amount of valid data items in the cross-covariance, thereby helping to improve the accuracy of the frequency analysis results. Furthermore, even in the case of a small number of receivers in the embodiments of the present application, the expansion vector r can be used to obtain a sufficient amount of data for frequency analysis and calculation, thereby helping to compress the width of the main lobe in the spatial spectrum and improve the frequency. The accuracy of the analysis results.

In a possible implementation manner, the expansion vector r can be constructed in the following manner, including: determining at least a pair of receivers corresponding to each vector element according to the flow parameter corresponding to each vector element; and obtaining the correspondence of each vector element In at least one pair of receivers, the cross-covariance of each pair of receivers; for each vector element, calculate the mean value of the cross-covariance of each pair of receivers in at least one pair of receivers to obtain the cross-covariance of each vector element Take a value; construct the extended vector r according to the value of each of the N vector elements.

Exemplarily, obtaining the cross-covariance of each pair of receivers in the at least one pair of receivers corresponding to each vector element may include: constructing a covariance matrix according to the signals received by the M receivers. The dimension is M×M, the matrix element in the mth row and nth column of the covariance matrix is used to indicate the cross-covariance between the mth receiver and the nth receiver, m and n are both [1,M] Integer in. Determine at least one matrix element corresponding to each flow parameter in the covariance matrix. According to at least one matrix element corresponding to each flow type parameter and each vector element corresponding to each flow type parameter, the mutual covariance of each pair of receivers in at least a pair of receivers corresponding to each vector element is determined. Then, the value of each vector element can be calculated according to the mutual covariance of each pair of receivers in at least one pair of receivers corresponding to each vector element, thereby constructing an extended vector r.

Exemplarily, the covariance matrix may satisfy the following formula:

Among them, R is the covariance matrix, and x(t) is the receiving vector composed of the sampling data of the signals received by the M receivers at the t-th sampling point.

In another possible implementation manner, the expansion vector r can be constructed in the following manner, including: determining at least one pair of receivers corresponding to each vector element according to the flow parameter corresponding to each vector element; , Obtaining the mutual covariance of any pair of receivers in the at least one pair of receivers corresponding to each vector element as the value of each vector element; and then according to the value of each vector element in the N vector elements Value, construct the expansion vector r.

In a possible implementation manner, in the M receivers, the cross-covariance between the m-th receiver and the n-th receiver satisfies the following formula:

Among them, x _m (t) is the sampling data of the signal received by the m-th receiver at the t-th sampling point, and x _n (t) is the sampling data of the signal received by the n-th receiver at the t-th sampling point Data, m and n are both integers in [1,M], T is the number of sampling points, and T is an integer greater than or equal to 1.

In a possible implementation manner, N is greater than or equal to M, and N is less than M ² -M+1; or, N is greater than M, and N is less than or equal to M ² -M+1. That is, N can be ^{any integer in [M, M 2} -M+1]. In the embodiment of the present application, the number of vector elements in the extension vector r is not less than the number of receivers. In the case of fewer receivers, the embodiment of the present application can increase the amount of data used for frequency analysis and calculation through the extension vector r. This is beneficial to compress the width of the main lobe in the spatial spectrum and improve the accuracy of the frequency analysis results.

In a possible implementation, the distance between any two adjacent receivers in the M receivers is an integer multiple of the unit distance; the flow parameter corresponding to each vector element is In at least a pair of receivers, the difference between the position coordinates of the first receiver in each pair of receivers minus the position coordinates of the second receiver, the position coordinates of the first receiver and the position coordinates of the second receiver All are based on the unit distance. Since the position coordinates of the first receiver and the second receiver are obtained according to the unit distance in the embodiment of the present application, the position coordinates of the first receiver and the second receiver can both be integers, so that the first receiver is relative to the first receiver. The order distance of the two receivers is an integer. In this case, it is helpful to simplify the subsequent frequency analysis and calculation.

In a possible implementation manner, the FFT calculation can be performed by extending the vector r. Specifically, it may include: according to the size order of the N flow type parameters, sequentially arranging the N vector elements corresponding to the N flow type parameters to obtain the reordered expansion vector

The extended vector

Perform Fourier transform FFT calculation to obtain FFT spatial spectrum. Using the frequency analysis method provided by the embodiment of the present application, compared with the traditional FFT calculation, the embodiment of the present application is beneficial to improve the accuracy and robustness of the FFT calculation result.

In another possible implementation manner, performing FFT calculation through the expansion vector r may also include: performing frequency analysis and calculation on the expansion vector r according to the N flow type parameters, including: according to the magnitude order of the N flow type parameters, Sequentially arrange the N vector elements corresponding to the N flow parameters to obtain the reordered expansion vector

If among the N flow pattern parameters arranged in sequence, the difference between two adjacent flow pattern parameters is P, and P is an integer greater than 1, then the reordered expansion vector is obtained

In, the vector elements corresponding to the two adjacent flow parameters include P-1 interpolation; the expansion vector of the rearrangement

Perform Fast Fourier Transform FFT calculation to obtain FFT spatial spectrum.

FFT calculation requires the sampling data of the received signal. The sampling data of the signal received by each receiver has continuous phases at equal intervals. Converting the sampling data of the received signal to a second-order statistics can obtain multiple cross-covariances. FFT calculation requires more The exponential coefficients of valid data items in the two cross-covariances are continuous. Among them, the exponential coefficient corresponds to the flow pattern parameter. For a non-uniform linear array, the N flow pattern parameters are often non-continuous, that is, among the N flow pattern parameters arranged in sequence, there may be a difference between two adjacent flow pattern parameters greater than 1, such as adjacent The difference between the two flow parameters of is P. In this case, the expansion vector is rearranged in order

, The vector elements corresponding to the two adjacent flow parameters include P-1 interpolations, so that the sequence of the expansion vector is rearranged

FFT calculation can be applied. The embodiment of the present application can implement FFT calculation in a non-uniform linear array, and compared with the traditional FFT calculation, the embodiment of the present application is beneficial to improve the accuracy and robustness of the FFT calculation result.

In yet another possible implementation manner, DBF calculation can also be performed by extending the vector r. Specifically, it may include: performing digital beamforming DBF calculation on the extension vector r, and the DBF calculation satisfies the following formula:

Among them, f _DBF (θ) is the DBF space spectrum,

For the steering vector constructed based on the expansion vector r and N flow pattern parameters, θ∈Θ, Θ is a set of discrete search intervals. Using the frequency analysis method provided by the embodiment of the present application, compared with the traditional DBF calculation, the embodiment of the present application is beneficial to improve the accuracy and robustness of the DBF calculation result.

In a possible implementation manner, the N flow type parameters may be determined according to the set elements in the difference co-array of the receiving array.

In a second aspect, an embodiment of the present application also provides a device that can be used to analyze signals received by M receivers, where the M receivers are linearly arranged, and M is an integer greater than 1. The device mainly includes an expansion unit and a calculation unit. Among them, the expansion unit is used to construct an expansion vector r including N vector elements. In the expansion vector r, N vector elements correspond to N flow-type parameters, where each vector The element is used to indicate the cross-covariance of at least a pair of receivers, and the flow parameter corresponding to each vector element is used to indicate that each vector element corresponds to at least a pair of receivers, and the first receiver in each pair of receivers is relative to The order distance of the second receiver; the calculation unit is used to perform frequency analysis and calculation on the expansion vector r according to the above-mentioned N flow pattern parameters.

In a possible implementation manner, the extension unit is specifically configured to: determine at least one pair of receivers corresponding to each vector element according to the flow parameter corresponding to each vector element; to obtain at least one pair of receivers corresponding to each vector element In the receiver, the cross-covariance of each pair of receivers; for each vector element, the value of each vector element is calculated according to the mean value of the cross-covariance of each pair of receivers in at least one pair of receivers; according to N The value of each vector element in the vector elements is used to construct the extended vector r.

In a possible implementation, the extension unit is specifically configured to: determine at least one pair of receivers corresponding to each vector element according to the flow parameter corresponding to each vector element; for each vector element, obtain each vector element In the corresponding at least one pair of receivers, the cross-covariance of any pair of receivers is used as the value of each vector element; the expansion vector r is constructed according to the value of each vector element in the N vector elements.

In a possible implementation, the expansion unit is specifically configured to: construct a covariance matrix according to the signals received by M receivers, the dimension of the covariance matrix is M×M, and the covariance matrix in the mth row and nth column Matrix elements are used to indicate the cross-covariance between the m-th receiver and the n-th receiver. Both m and n are integers in [1,M]; in the determination of the covariance matrix, each flow type parameter corresponds to each According to at least one matrix element corresponding to each flow type parameter, and each vector element corresponding to each flow type parameter, determine at least one pair of receivers corresponding to each vector element, and each pair receives The cross-covariance of the detector.

In a possible implementation, the covariance matrix satisfies the following formula:

In a possible implementation manner, N is greater than or equal to M, and N is less than M ² -M+1; or, N is greater than M, and N is less than or equal to M ² -M+1.

In a possible implementation, the distance between any two adjacent receivers in the M receivers is an integer multiple of the unit distance; the flow parameter corresponding to each vector element is In at least a pair of receivers, the difference between the position coordinates of the first receiver in each pair of receivers minus the position coordinates of the second receiver, where the position coordinates of the first receiver and the position coordinates of the second receiver All are based on unit distance.

In a possible implementation manner, the calculation unit is specifically configured to: according to the size order of the N flow pattern parameters, sequentially arrange the N vector elements corresponding to the N flow pattern parameters to obtain the reordered expansion vector

Reordered expansion vector

Perform Fourier transform FFT calculation to obtain FFT spatial spectrum.

In a possible implementation manner, the calculation unit is specifically configured to: according to the size order of the above N flow pattern parameters, sequentially arrange the N vector elements corresponding to the N flow pattern parameters to obtain the reordered expansion vector

Perform Fast Fourier Transform FFT calculation to obtain FFT spatial spectrum.

In a possible implementation manner, the calculation unit is specifically configured to: perform digital beamforming DBF calculation on the extension vector r, and the DBF calculation satisfies the following formula:

Among them, f _DBF (θ) is the DBF space spectrum,

For the steering vector constructed based on the expansion vector r and N flow pattern parameters, θ∈Θ, Θ is a set of discrete search intervals.

In a possible implementation manner, the N flow parameters are determined according to the set elements in the difference co-array of the receiving array.

In a third aspect, an embodiment of the present application provides a device that includes a processor and a memory, where the memory is used to store computer programs or instructions; the processor is used to execute the computer programs or instructions stored in the memory, so that the The device executes the frequency analysis method as provided in any one of the first aspect.

In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium in which a computer program or instruction is stored. When the computer reads and executes the computer program or instruction in the computer-readable storage medium , To make the computer execute the frequency analysis method provided in any one of the first aspect.

In a fifth aspect, an embodiment of the present application provides a radar, including a transmitter, a receiving array, and a frequency analysis device. The receiving array includes M linearly arranged receivers, where M is an integer greater than 1, and the transmitter uses In transmitting the detection signal; the receiving array is used to receive the echo signal; the frequency analysis device is used to perform frequency analysis on the received signal of the receiving array according to the frequency analysis method provided in any one of the first aspect , Wherein the received signal of the receiving array includes the above-mentioned echo signal.

In a sixth aspect, an embodiment of the present application provides a program product, which when a computer reads and executes the computer program product, causes the computer to execute the frequency analysis method provided in any one of the above.

These and other aspects of the present application will be more concise and understandable in the description of the following embodiments.

Description of the drawings

Figure 1 is a schematic diagram of a radar structure;

Figure 2 is a schematic diagram of a uniform linear array structure;

Figure 3 is a schematic diagram of a non-uniform linear array structure;

Figure 4 is a schematic diagram of a non-uniform linear array structure;

FIG. 5 is a schematic flowchart of a frequency analysis method provided by an embodiment of this application;

FIG. 6 is a schematic diagram of comparison of FFT calculation results in a uniform linear array according to an embodiment of the application;

Figure 7 is a schematic diagram of a non-uniform linear array structure;

FIG. 8 is a schematic diagram of comparison of FFT calculation results in a non-uniform linear array according to an embodiment of the application;

FIG. 9 is a schematic diagram of a comparison of DBF calculation results in a uniform linear array according to an embodiment of the application;

FIG. 10 is a schematic diagram of a comparison of DBF calculation results in a non-uniform linear array according to an embodiment of the application;

FIG. 11 is a schematic structural diagram of a device provided in an embodiment of the application;

FIG. 12 is a schematic diagram of the structure of an apparatus provided in an embodiment of the application.

Detailed ways

In order to make the purpose, technical solutions, and advantages of the application more clear, the application will be further described in detail below with reference to the accompanying drawings. The specific operation method in the method embodiment can also be applied to the device embodiment or the system embodiment. It should be noted that in the description of this application, "at least one" refers to one or more, and multiple refers to two or more. In view of this, in the embodiments of the present invention, “a plurality of” may also be understood as “at least two”. "And/or" describes the association relationship of the associated objects, indicating that there can be three types of relationships, for example, A and/or B, which can mean: A alone exists, A and B exist at the same time, and B exists alone. In addition, the character "/", unless otherwise specified, generally indicates that the associated objects before and after are in an "or" relationship. In addition, it should be understood that in the description of this application, words such as "first" and "second" are only used for the purpose of distinguishing description, and cannot be understood as indicating or implying relative importance, nor can it be understood as indicating Or imply the order.

The technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application.

At present, receiving arrays are used in many electronic devices. The receiving array includes multiple receivers arranged in an array, and each receiver can receive external signals, that is, the received signal of the receiving array includes signals received by the multiple receivers.

Since different receivers in the receiving array receive different signals, it is necessary to perform frequency analysis on the received signals of the receiving array. For example, due to the different positions of the receivers in the receiving array, the phases of the target signals received by different receivers are also different for the same target signal. Through frequency analysis of the received signal of the receiving array, the direction of arrival of the target signal can be estimated based on the relationship between the position of each receiver and the phase of the target signal received by each receiver.

It should be understood that the embodiments of the present application are applicable to multiple types of receivers. For example, the receiver-antenna in millimeter wave radar, the receiver-photodetector in laser radar, and various types of sensors in sonar and medical equipment. Depending on the type of receiver, the type of signal received by the receiver is also different. For example, the echo signal received by the antenna in the millimeter wave radar is a millimeter wave signal, and the echo signal received by the photodetector in the laser radar is a laser signal. In order to facilitate understanding, the embodiments of the present application are described by taking a radar as an example in the following. The radar may be a millimeter wave radar, a lidar, or an infrared radar. The embodiments of the present application do not limit this.

FIG. 1 exemplarily shows a schematic diagram of a radar structure. As shown in FIG. 1, the radar 100 mainly includes a transmitter 101, a receiving array 102 and a frequency analysis device 103. Among them, the transmitter 101 can transmit a detection signal, and the receiving array 102 can receive the detection signal reflected by the object under test, that is, the echo signal. It should be understood that the received signal of the receiving array 102 includes signals received by M receivers, and the received signal of the receiving array 102 includes both echo signals and noise signals.

The frequency analysis device 103 may be a processing chip inside the radar 100, for example, it may be a central processing unit (CPU) of the radar 100, or a system on chip (SoC) of the radar 100. The frequency analysis device 103 can perform frequency analysis on the received signal of the receiving array 102. Specifically, when the frequency analysis device 103 performs frequency analysis on the received signal of the receiving array, it generally performs processing based on the sampling data of the received signal of the receiving array 102. Exemplarily, a sampler 104 is provided in the radar 100, and the sampler 104 may be an analog-to-digital converter (ADC). The sampler 104 may intercept a portion of the received signal from the receiving array 102 as sample data at a certain interval, and the processor 103 may perform frequency analysis on the received signal of the receiving array 102 according to the sampled data provided by the sampler 104. The time point of sampling by the sampler 104 may also be referred to as a sampling point.

Generally speaking, after frequency analysis, the frequency analysis device 103 can obtain the direction of arrival (reception angle) of K echo signals in the received signal. K is an integer greater than or equal to 1, and the K echo signals can also be called K target signals.

Alternatively, after frequency analysis, the frequency analysis device 103 may also obtain the spatial spectrum of the received signal of the receiving array 102. Specifically, the spatial spectrum is mainly expressed as an angle-intensity curve, that is, the intensity of the received signal at different angles. Generally speaking, in the incoming direction of any target signal, the intensity of the target signal and the intensity of the noise signal are superimposed, so that the signal intensity corresponding to the incoming direction is significantly increased, and the intensity in the angle-intensity curve of the spatial spectrum is significantly increased. The part is also called the main lobe of the spatial spectrum. Therefore, after the spatial spectrum is obtained, the direction of arrival of K target signals in the received signal can be estimated according to the angle corresponding to the main lobe in the spatial spectrum.

However, as the integration of the radar 100 increases, the space available for installing the receiving array 102 in the radar 100 is limited, resulting in an insufficient number of receivers in the receiving array 102. Moreover, in order to reduce the cost of the radar 100, some manufacturers will omit part of the receivers in the receiving array 102, so that the receiving array 102 is arranged unevenly.

The above various factors lead to insufficient data available for frequency analysis during frequency analysis, which is not conducive to improving the accuracy of frequency analysis, and further affects the robustness and accuracy of radar detection results. For example, due to insufficient data for frequency analysis, the main lobe in the calculated spatial spectrum is too wide, and the side lobes in the spatial spectrum may also increase, resulting in insufficiently accurate estimation results of the direction of arrival of K target signals.

In view of this, an embodiment of the present application provides a frequency analysis method, which can be applied to the frequency analysis device 103. The frequency analysis method provided in the embodiments of the present application can be applied to both linear arrays and square arrays. Specifically, according to the arrangement of the receivers in the receiving array 102, the receiving array 102 can be divided into a linear array and a square array. Among them, the multiple receivers of the linear array are arranged linearly. The multiple receivers of the square array are arranged in multiple rows and multiple columns. Generally, when performing frequency analysis on the signal received by the square array, you can first analyze the signal received by each row of the square array according to the method of linear array analysis, and then combine the analysis results of the line-by-line analysis to get The analysis result of the received signal of the square matrix.

For ease of description, the following takes a linear array as an example for description. It should be pointed out that the frequency analysis method provided in the embodiment of the present application can also be applied to the frequency analysis of the received signal of the square array, which will not be repeated here.

Fig. 2 exemplarily shows a schematic diagram of a possible receiving array structure. As shown in Figure 2, the receiving array includes M linearly arranged receivers. In Figure 2, the M receivers respectively correspond to the digital serial numbers "1,2,3....M" in the order from left to right, which means that the receiver array is the first receiver and the second receiver in order from left to right. Receivers, 3rd receiver, ..., Mth receiver.

It should be pointed out that the numerical sequence number corresponding to each receiver in FIG. 2 is only for exemplarily distinguishing each receiver of the receiving array, so as to describe the method provided by the embodiment of the present application. The numerical sequence number in FIG. 2 does not constitute a substantial limitation on the structure of the receiving array. For example, the M receivers can also be described as "the first receiver, the second receiver, the third receiver, ..., the M-th receiver" in the order from left to right. The M receivers can be described as "the first receiver, the second receiver, the third receiver, ..., the M-th receiver" in other order. The M receivers in the receiving array can be either a linear arrangement in the left-right direction, a linear arrangement in the up-down direction, or a linear arrangement in any other oblique direction. In short, the description order of the M receivers and the arrangement direction of the M receivers do not affect the specific implementation of the embodiments of the present application, and details are not repeated here. Exemplarily, the embodiments of the present application are described in the following by taking the numerical sequence number shown in FIG. 2 as an example.

In the embodiment of the present application, there are multiple linear arrangements of the M receivers in the receiving array. For example, in the receiving array shown in Figure 2, the distance between any two adjacent receivers is d, so the receiving array shown in Figure 2 can also be called a uniform linear array, and d can be called a receiving array. The unit distance. At present, in order to reduce the cost of the receiving array, some manufacturers will omit the receivers in some locations. This receiving array can also be called a non-uniform linear array. In a non-uniform linear array, the distance between any two adjacent receivers may be the unit distance d or multiple times the unit distance d. As shown in Figure 3, the distance between the first receiver and the second receiver is 2d, and the distance between the second receiver and the third receiver is d. It can be understood that the unit distance d can be any possible value under the premise that the receiving array is capable of receiving. For example, the unit distance d can be the half-wavelength, wavelength, or other possible distance length of the target signal. The implementation of this application The example does not restrict this much.

In the embodiment of the present application, the receiving array corresponds to a plurality of flow type parameters, and the number of flow type parameters and the specific value of each flow type parameter are all related to the arrangement of M receivers. In other words, for the frequency analysis device 103, multiple flow pattern parameters corresponding to the receiving array 102 can be used as known parameters for frequency analysis. Specifically, M receivers may constitute M ² pairs of receivers, and each pair of receivers includes a first receiver and a second receiver. Wherein, the first receiver may be the m-th receiver, and the second receiver may be the n-th receiver. In the M ² pair of receivers, m and n traverse from 1 to M in sequence.

The order distance corresponding to each pair of receivers refers to the order distance of the first receiver relative to the second receiver in each pair of receivers. The order distance can be understood as the first receiver relative to the second receiver And the distance between the first receiver and the second receiver. Among the M ² pairs of receivers, any two pairs of receivers may correspond to the same order distance or may correspond to different order distances.

In the embodiment of the present application, the N flow pattern parameters corresponding to the receiving array may indicate the N types of ordered distances existing in the ^{M 2 pair receiver.} Exemplarily, the N flow pattern parameters may be equivalent to the N types of ordered distances existing in the ^{M 2 pair receiver.} It can be understood that there may also be a more complicated correspondence between the N flow pattern parameters and the N ordered distances, which will not be repeated in the embodiment of the present application.

Generally speaking, N is greater than or equal to M, and N is less than M ² -M+1; or, N is greater than M, and N is less than or equal to M ² -M+1. That is, N can be ^{any positive integer in [M, M 2} -M+1].

Exemplarily, ^{the ordered distances corresponding to the receivers by M 2} can be as shown in Table 1 below:

Table I

Among them, dm represents the position coordinates of the m-th receiver, dn represents the position coordinates of the n-th receiver, and both m and n traverse from 1 to M. Exemplarily, the first row and the first column in Table 1 indicate that the first receiver and the second receiver are both the first receiver, so the order distance of the first receiver relative to the second receiver is zero. In the first row and second column of Table 1, the first receiver is the first receiver and the second receiver is the second receiver. Therefore, the order distance of the first receiver relative to the second receiver is d1 -d2, where d1 is the position coordinate of the first receiver. d2 is the position coordinate of the second receiver.

It can be understood that the absolute value of dm-dn in Table 1 can indicate the distance between the m-th receiver and the n-th receiver, and the positive or negative of dm-dn can indicate that the m-th receiver is relative to the n-th receiver. The direction of the device. For example, if dm-dn is positive, it means that the m-th receiver is located in the first direction of the n-th receiver. If dm-dn is negative, it means that the m-th receiver is located in the second direction of the n-th receiver. Direction, the first direction and the second direction are two opposite directions parallel to the receiving array (linear array). Therefore, dm-dn can be used as the ordered distance corresponding to a pair of receivers formed by the m-th receiver and the n-th receiver, that is, the ordered distance of the m-th receiver relative to the n-th receiver.

^{Assuming that there are N different values in the ordered distances respectively corresponding to the M 2} pairs of receivers in Table 1, N flow parameters of the receiving array can be obtained according to the values of the N different ordered distances. For example, the N ordered distances with different values can be used as the flow parameter of the receiving array, and the N reduction results obtained by dividing the N ordered distances with different values by the greatest common divisor can be used as the receiving array. The flow pattern parameters of, etc., which are not listed one by one in the embodiment of this application.

In a possible implementation manner, in a uniform linear array or a non-uniform linear array, position coordinates can be assigned to each receiver according to the unit distance d. Taking the uniform linear array shown in Figure 2 as an example, assuming that the first receiver is the origin of coordinates, the position coordinates of the first receiver to the M-th receiver are: 0, 1, 2, ..., M- 1. On this basis, Table 1 can be simplified to Table 2 as follows:

Table II

It can be seen from Table 2 that by assigning position coordinates to each receiver according to the unit distance d, ^{the ordered distances corresponding to the receivers by M 2} can be all positive integers, which is beneficial to simplify subsequent calculations. Taking Table 2 as an example, the N flow parameters are specifically: 1-M, 2-M, ..., 0, 1, 2, ..., M-1, a total of 2M-1 flow parameters, that is, N= 2M-1.

Another example is the non-uniform linear array shown in Figure 4, which includes a total of 5 receivers. The second receiver and the first receiver are separated by 2d, and the third receiver and the second receiver are separated by 2d. And the distance between the fourth receiver and the third receiver is d, and the distance between the fifth receiver and the fourth receiver is 2d. Assuming that the first receiver is the origin of the coordinates, the position coordinates of the five receivers are allocated according to the unit distance d, and the position coordinates of the first to fifth receivers are 0, 2, 3, 4, and 6 in order.

In this case, Table 1 can be simplified to:

Table Three

Based on the order distances corresponding to the 25 pairs of receivers shown in Table 3, the receiving array shown in Figure 4 has 11 flow parameters, which are: -6, -4, -3,- 2, -1, 0, 1, 2, 3, 4, and 6.

In a possible implementation manner, the N flow parameters of the receiving array may be determined according to the set elements in the difference co-array of the receiving array. The differential co-array set of the receiving array satisfies the following formula:

D={d _m -d _n |m,n∈[1,M]} (Formula 1)

Among them, D represents the differential co-array set of the receiving array, dm is the position coordinate of the m-th receiver, dn is the position coordinate of the n-th receiver, and both m and n traverse from 1 to M.

In the embodiment of the present application, when the arrangement of the M receivers of the receiving array is known, the differential co-array set of the receiving array can be calculated according to the position coordinates of the M receivers, and the set elements of the differential co-array set Determine the N flow type parameters. Exemplarily, N set elements in the differential co-array set can be used as the N flow type parameters of the receiving array.

In order to improve the robustness and accuracy of frequency analysis, the embodiment of the present application uses the second-order statistical characteristics of the received signal and the N flow pattern parameters of the receiving array to construct an extended vector r, and performs frequency analysis on the extended vector r, which is beneficial to Increasing the amount of data available for frequency analysis will help improve the robustness and accuracy of the frequency analysis results.

Next, the frequency analysis method provided in the embodiment of the present application will be further illustrated by way of example. FIG. 5 exemplarily shows that an embodiment of the present application provides a frequency analysis method, which can be used to analyze the signals received by the M receivers in FIG. 2, that is, the received signals of the receiving array 102. As shown in Figure 5, the frequency analysis method mainly includes the following steps:

S501: Construct an extended vector r including N vector elements.

In the embodiment of the present application, the N vector elements in the extension vector r correspond to the N flow type parameters. Specifically, the extension vector r may include at least N vector elements, and the relationship between the at least N vector elements and the N flow type parameters may be one-to-one or many-to-one. It can also be understood that, among the N flow type parameters, each flow type parameter corresponds to one or more vector elements. Exemplarily, for FFT calculation or DBF calculation, the expansion vector r includes N vector elements, and the N vector elements correspond to N flow type parameters in a one-to-one correspondence.

Exemplarily, the expansion vector r can be expressed as:

r=[r1,r2,…,rN] (Formula 2)

Among them, r1, r2,..., rN can represent N vector elements of the extended vector r. In the embodiment of the present application, each vector element of the extension vector r may indicate the mutual covariance of at least a pair of receivers. Taking the vector element r1 as an example, suppose that the vector element r1 corresponds to the flow parameter △d1, ^{and the order distance of the E pair of receivers in the M 2} pair of receivers is △d1, then the vector element r1 corresponds to the E pair of receivers , The vector element r1 can indicate the cross-covariance of the E to the receiver. E is an integer greater than or equal to 1.

S502: Perform frequency analysis on the expansion vector r according to the N flow type parameters.

Next, the principle of the embodiments of the present application will be briefly described:

The sampling data X of the received signal of the receiving array at T sampling points can be expressed as:

X=[x(1),x(2),…,x(t),…,x(T)] (Formula 3)

Among them, x(t) is the received vector of the received signal at the t-th sampling point, t is an integer in [1, T], and T is an integer greater than or equal to 1.

For the received vector x(t) at the t-th sampling point, it satisfies the following formula:

Among them, A is the array flow matrix of the receiving array, s(t) is the target signal waveform, and n(t) is the additive Gaussian noise term.

Specifically, s(t) can be expressed as s(t)=[s ₁ (t),...,s _k (t),...,s _K (t)] ^T , k is the value in [1,K] Any integer, K is the number of target signals in the received signal of the receiving array, and s _k (t) is the waveform of the k-th target signal.

A can be expressed as A=[a(θ ₁ ),...a(θ _k ),...,a(θ _K )], θ _k is the direction of arrival of the k-th target signal, where the k-th target signal The direction of the incoming wave can also be understood as the angle at which the k-th target signal illuminates the receiving array. a(θ _k ) is the steering vector corresponding to the k-th target signal, which satisfies the following formula:

Among them, d1 to dM are the position coordinates of the 1st to Mth receivers respectively.

λ is the wavelength of the K echo signals. Generally speaking, the wavelength of the K echo signals is the same as the wavelength of the detection signal.

The second-order statistical characteristics of the received signal can be expressed as the construction of an M×M covariance matrix based on the signals received by M receivers, and the covariance matrix satisfies the following formula:

Among them, R is the covariance matrix, and the M ² matrix elements of the covariance matrix R respectively correspond to the cross covariance of the ^{M 2 pairs of receivers.}

Specifically, the cross-covariance of a pair of receivers refers to the signal received by the first receiver (such as the m-th receiver) and the signal received by the second receiver (such as the n-th receiver) in a pair of receivers. The covariance between the received signals. _{Exemplarily, the cross-covariance R {m,n}} between the m-th receiver and the n-th receiver may satisfy the following formula:

Among them, x _m (t) is the sampling data of the signal received by the m-th receiver at the t-th sampling point, and x _n (t) is the signal received by the n-th receiver at the t-th sampling point Sampled data.

In the embodiment of the present application, it may be assumed that the target signals are not correlated with each other, the target signals and the noise signals are not correlated with each other, and the noise signals are not correlated with each other. Exemplarily, it can be represented by the following three formulas:

The target signals are not related to each other:

Among them, s _i (t) represents the sampling data of the i-th target signal at the t-th sampling point, and s _j (t) represents the sampling data of the j-th target signal at the t-th sampling point.

Each target signal and each noise signal are not correlated with each other:

Among them, n _j (t) represents the sampling data of the j-th noise signal at the t-th sampling point.

The various noise signals are not correlated with each other:

Among them, n _i (t) represents the sampling data of the i-th noise signal at the t-th sampling point.

Introducing formula 8 to formula 10 into the covariance matrix R, the covariance matrix R shown in formula 6 can be further transformed into:

among them,

I _M represents a unit diagonal matrix with a dimension of M×M.

The covariance matrix R is essentially the second-order statistic of the received signal, where AR _s A ^H is a valid data item,

Is the noise term. Introducing the irrelevant characteristics shown in formulas 8 to 10, R _s can be transformed into a diagonal matrix whose diagonal elements are the power of the target signal. The noise term in formula 11

It becomes a constant related to the signal strength of the noise signal.

Specifically, the matrix element in the mth row and nth column of the covariance matrix can be understood as the cross-covariance R _{m,n} between the m-th receiver and the n-th receiver, and R _{m,n} also satisfies The following formula:

among them,

Indicates the signal strength of the k-th target signal.

The nth statistic representing the signal strength of the noise signal,

Can be understood as a constant, that is,

The value of has nothing to do with the value of n.

Exemplarily, for the uniform linear array shown in FIG. 2, in the case of allocating position coordinates for M receivers according to the unit distance d, the covariance matrix can be expressed as:

It can be seen from Formula 12 and Formula 13 that _{the value of R {m,n}} is mainly related to d _m -d _n and μ _k , where μ _k is the sin function of the incoming wave direction θ _k. Therefore, when performing frequency analysis, _{the cross-covariance corresponding to different exponential coefficients d m} -d _n contains most of the angle information of the received signal. In other words, the frequency analysis can be performed on the cross-covariance corresponding to the _{exponential coefficients d m} -d _{n of different values.} Among them, the exponential coefficient d _m -d _n can be understood not only as the ordered distance of the m-th receiver relative to the n-th receiver, but also as the flow parameter of the receiving array.

In view of this, the N vector elements in the extension vector r constructed according to the N flow parameters in the embodiment of the present application include all the angle information of the received signal. Perform frequency analysis on the extension vector r to obtain the received signal and the direction of the incoming wave. Related parameters. For example, the direction of arrival of K target signals can be obtained, or the spatial spectrum of the receiving action can be obtained.

The expansion vector r in the embodiment of the present application is constructed on the basis of the second-order statistical characteristics (cross-covariance) of the received signal and the arrangement structure (N flow parameters) of the receiving array. The value of the vector element N in the extension vector r is not less than the number of receivers M. Compared with directly performing frequency analysis on the received signals of M receivers, the embodiment of the present application is beneficial to increase the amount of data for frequency analysis, and They are all valid data, which helps to improve the accuracy of frequency analysis. Moreover, the embodiments of the present application are based on the second-order statistical characteristics of the received signal, which is beneficial to improve the robustness of the analysis result.

In the extended vector r of the embodiment of the present application, the flow type parameter corresponding to each vector element is used to indicate that in at least one pair of receivers corresponding to each vector element, the first receiver in each pair of receivers is relative to the second receiver. The ordered distance of the device. Exemplarily, the extension vector r can be constructed by at least the following two implementation methods:

In the first possible implementation, the expansion vector r can be constructed through the following steps:

Step 1: Determine at least one pair of receivers corresponding to each vector element according to the flow parameter corresponding to each vector element. For example, if the vector element r1 corresponds to the flow parameter Δd1, the E pair of receivers with an orderly distance of Δd1 is selected ^{from the M 2 pairs of receivers.} The vector elements r2 to rN are the same, so I won’t repeat them here.

Step 2A: Obtain the cross-covariance of each pair of receivers in at least one pair of receivers corresponding to each vector element. For example, if the vector element r1 corresponds to an E pair of receivers, the cross-covariance of the E pair of receivers can be calculated separately. The vector elements r2 to rN are the same, so we won't repeat them.

In a possible implementation of step 2A, the cross-covariance of each pair of receivers can be calculated separately according to formula 7. In another possible implementation of step 2A, the cross-covariance formula can also be constructed according to formula 12. Furthermore, at least one matrix element corresponding to each flow parameter in the covariance matrix can be determined.

Specifically, the matrix element R _{m,n} can represent the cross-covariance between the m-th receiver and the n-th receiver, which corresponds to the flow parameter dm-dn. Next, according to at least one matrix element corresponding to each flow type parameter, and each vector element corresponding to each flow type parameter, determine the at least one pair of receivers corresponding to each vector element. Cross-covariance.

For example, the vector element r1 corresponds to the flow pattern parameter Δd1, and the E matrix elements corresponding to the flow pattern parameter Δd1 can be determined from the covariance matrix. The E matrix elements can be used as the cross-covariance of E to the receiver corresponding to the vector element r1.

Step 3: For each vector element, calculate the value of each vector element according to the mean value of the cross-covariance of each pair of receivers in at least one pair of receivers. For example, for the E pair of receivers corresponding to the vector element r1, the average value of the cross-covariance of the E pair of receivers is calculated, and the calculated average value can be used as the value of the vector element r1. The vector elements r2 to rN are the same, so I won’t repeat them here.

Step 4: Construct an extended vector r according to the value of each of the N vector elements.

In the second possible implementation manner, after step one above, you can also continue to perform step two B: for each vector element, obtain at least one pair of receivers corresponding to each vector element, Cross covariance, as the value of each vector element. For example, for the aforementioned vector element r1, any pair of receivers can be selected from the E pair of receivers corresponding to the vector element r1, and the cross-covariance of the pair of receivers can be calculated as the value of the vector element r1. The vector elements r2 to rN are the same, so I won’t repeat them here. After that, you can continue to perform step four to complete the construction of the expansion vector r.

In the embodiment of the present application, the expansion vector r can be applied to various frequency analysis calculations. In other words, there are multiple possible calculation methods for the frequency analysis calculation in S502. Next, take FFT calculation and DBF calculation as examples to further illustrate the embodiments of the present application. It should be pointed out that the extension vector r provided in the embodiments of the present application can also be used in other frequency analysis calculation methods, such as using multiple signal classification algorithms (MUSIC) after performing spatial smoothing operations on the extension vector r, etc. Super-resolution algorithm calculations will not be listed one by one.

At present, FFT calculation can calculate the sampling data x(t) of the received signal at the t-th sampling point to obtain the FFT spatial spectrum of the received signal. This calculation method does not fully utilize the second-order statistical characteristics of the received signal, and requires the phase of the sampled data to be continuous at equal intervals, that is, the FFT calculation requires the receiving array to be a uniform linear array. For non-uniform linear arrays, the calculation result of FFT calculation is not ideal. Moreover, the data amount of x(t) is determined by the number of receivers in the receiving array, that is to say, when the number of receivers in the receiving array is insufficient, the accuracy of the calculation result of the FFT calculation is often not high.

In the embodiment of the present application, the expansion vector r may be used to implement FFT calculation to obtain the FFT spatial spectrum of the received signal. It is helpful to improve the accuracy and robustness of the calculation result of FFT calculation. Exemplarily, first, according to the size order of the N flow type parameters, the N vector elements corresponding to the N flow type parameters can be sequentially arranged to obtain the reordered expansion vector.

Reorder the expanded vector

Perform Fourier transform FFT calculation to obtain FFT spatial spectrum.

For example, the expansion vector r=[r1, r2,..., rN], the N vector elements r1 to rN in the expansion vector r correspond to N flow type parameters: Δd1 to ΔdN. When performing the FFT calculation, you can first arrange the vector elements r1 to rN in order according to the size order of the flow parameters △d1 to △dN to obtain the reordered expansion vector

Specifically, the vector elements r1 to rN can be arranged in the order of Δd1 to ΔdN from small to large, or the vector elements r1 to rN can be arranged in the order of Δd1 to ΔdN from large to small. For example, if delta d1 to delta dN increase in sequence, the expansion vector of the sequence rearrangement

Or, the reordered expansion vector

It can be understood that the embodiments of the present application do not limit the order of the magnitudes of △d1 to △dN. For example, the maximum value of △d1 to △dN can be △d1 or △dN, or other than △d1 and △dN. Any flow type parameter other than that. The minimum value of Δd1 to ΔdN can be Δd1, ΔdN, or any flow parameter except Δd1 and ΔdN.

It should be pointed out that the embodiment of the present application is also suitable for performing FFT calculation on a non-uniform linear array. Taking the non-uniform linear array shown in Figure 4 as an example, when the position coordinates of each receiver are allocated according to the unit distance d, the flow parameters of the receiving array are: -6, -4, -3, -2,- 1, 0, 1, 2, 3, 4, and 6. Correspondingly, the expansion vector r=[r1, r2,..., r11].

Assume that the correspondence between 11 vector elements and 11 flow parameters satisfies the following Table 4:

Table Four

流型参数Flow parameter	-6-6	-4-4	-3-3	-2-2	-1-1	00	11	22	33	44	66
向量元素Vector element	r1r1	r3r3	r5r5	r7r7	r9r9	r11r11	r10r10	r8r8	r6r6	r4r4	r2r2

Assuming that the 11 vector elements of the expansion vector r can be arranged as follows: r1, r3, r5, r7, r9, r11, r10, r8, r6, r4, and r2 in the descending order of the 11 flow type parameters.

If among the N flow parameters arranged in sequence, the difference between two adjacent flow parameters is P, and P is an integer greater than 1, then the expansion vector of the sequence rearrangement

, The vector elements corresponding to the two adjacent flow pattern parameters respectively include P-1 interpolation values.

For example, in Table 4, the difference between the process parameter -6 and -4 is 2, and the expansion vector is rearranged in order

In the vector element r1 and r3 also includes an interpolation. The same is true between vector elements r4 and r2, including an interpolation. Exemplary, rearranged expansion vector

Among them, c1 and c2 are interpolation. In the embodiment of the present application, the interpolation may be a default value, such as 0, or may also be a Newton interpolation, or it may also be a Lagrangian interpolation, which is not limited in the embodiment of the present application.

Furthermore, the reordered expansion vector can be

Perform FFT calculation to obtain FFT spatial spectrum.

In addition, the embodiment of the present application also simulates the application of FFT calculation in a uniform linear array. This simulation uses a uniform linear array composed of 20 receivers, and the distance between the array elements (that is, the unit distance) is the half-wavelength of the target signal. The number of sampling points T=100, and the signal-to-noise ratio (signal noise ratio, SNR) is 10dB. The number of target signals K=2, and the direction of arrival of the two target signals is set to ±4°.

Fig. 6 exemplarily shows two FFT space spectra, where the first FFT space spectrum is the FFT space spectrum obtained by the embodiment of the present application, and the second FFT space spectrum is the FFT space spectrum obtained by traditional FFT calculation. In the two FFT spatial spectra shown in Fig. 6, the abscissa represents the angle θ with a unit of degree (°), and the ordinate represents the signal strength with a unit of (dB). As shown in FIG. 6, compared with the FFT space spectrum obtained by traditional FFT calculation, in the FFT space spectrum obtained by the embodiment of the present application, the main lobe is narrower, and the main lobe is significantly higher than the side lobe. This is because the embodiment of the present application uses the second-order statistical characteristics of the received signal, which makes the result more robust and robust. At the same time, the expansion vector r increases the amount of data that can be used for FFT calculation, making the main lobe of the spatial spectrum narrower. It can be seen that the embodiments of the present application can improve the robustness and accuracy of FFT calculation in a uniform linear array.

In addition, the embodiment of the present application also simulates the application of FFT calculation in a non-uniform linear array. This simulation uses a non-uniform linear array as shown in Figure 7. According to the unit distance d, the position coordinates are assigned to the 4 receivers: the position coordinate of the first receiver d1=0, the position coordinate of the second receiver d2=1, the position coordinate of the third receiver d3=4, The position coordinate of the fourth receiver is d4=6. The receiving array can form 16 pairs of receivers, and the order distance corresponding to each pair of receivers can be as shown in Table 5 below:

Table 5

The flow parameter of the receiving array can be: -6, -5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5, and 6.

Based on the receiving array shown in Fig. 7, T sampling points are set in this simulation, and SNR=10dB. The direction of arrival of the two target signals is set to ±10°. If the traditional FFT calculation is used, x(t) only includes the sampling data of the received signals of the 4 receivers, and the amount of data is insufficient. However, the embodiment of the present application constructs an extension vector r, which includes 13 vector elements that can be used. It can be seen that the embodiment of the present application can increase the amount of data available for frequency analysis and calculation.

The simulation result can be shown in Figure 8. Fig. 8 exemplarily shows two FFT space spectra, where the first FFT space spectrum is the FFT space spectrum obtained by the embodiment of the present application, and the second FFT space spectrum is the FFT space spectrum obtained by traditional FFT calculation. In the two FFT spatial spectra shown in Fig. 8, the abscissa represents the angle θ with a unit of degree (°), and the ordinate represents the signal strength with a unit of (dB). It can be seen from Fig. 8 that the traditional FFT calculation is almost ineffective, and the main lobe and side lobes can hardly be distinguished in the FFT space spectrum. However, by using the embodiment of the present application for FFT calculation, a relatively obvious main lobe can still be obtained. It can be seen that the embodiment of the present application can also improve the accuracy and robustness of the FFT calculation in a non-uniform linear array.

DBF calculation is another commonly used frequency analysis algorithm. In the traditional DBF algorithm, it is necessary to construct the covariance matrix and steering vector of the received signal first, and then calculate the DBF space spectrum based on the covariance matrix and steering vector. But this kind of DBF calculation is still limited by the number of receivers. Moreover, for non-uniform linear arrays, the space spectrum obtained by the traditional DBF algorithm also has the problem of too high side lobes.

In the embodiment of the present application, the expansion vector r may be used to implement DBF calculation to obtain the DBF spatial spectrum of the received signal. It is beneficial to improve the accuracy and robustness of the calculation results of the DBF calculation. Exemplarily, the DBF calculation in the embodiment of the present application satisfies the following formula:

Among them, f _DBF (θ) is the DBF space spectrum,

Specifically,

It includes N vector elements, and the N vector elements have a one-to-one correspondence with N flow type parameters, and,

The arrangement order of the N vector elements in and the arrangement order of the N vector elements in the extended vector r both correspond to the arrangement order of the N flow type parameters. For example, suppose that the vector element r1 in the expansion vector r is the first vector element of the expansion vector r, and the vector element r1 corresponds to the flow parameter △d1, then

The first vector element in also corresponds to the flow parameter Δd1. Among the N vector elements, each vector element can be expressed in exponential form, and the exponential coefficient is the flow pattern parameter corresponding to the vector element. E.g,

The first vector element in also corresponds to the flow parameter △d1, then

The first vector element in can be expressed as:

The same is true for the other N-1 vector elements and will not be repeated here.

In addition, the embodiment of the present application also simulates the application of DBF calculation in a uniform linear array. The conditions set in this simulation are the same as the simulation conditions in the implementation of the third uniform linear array, and will not be repeated.

FIG. 9 exemplarily shows two DBF space spectra, where the first DBF space spectrum is the DBF space spectrum obtained by the embodiment of the present application, and the second DBF space spectrum is the DBF space spectrum obtained by traditional DBF calculation. In the two DBF spatial spectra shown in Fig. 9, the abscissa represents the angle θ, the unit is degrees (°), and the ordinate represents the signal strength, the unit is (dB). As shown in FIG. 9, compared with the DBF space spectrum obtained by traditional DBF calculation, in the DBF space spectrum obtained by the embodiment of the present application, the main lobe is narrower, and the main lobe is significantly higher than the side lobe. It can be seen that in a uniform linear array, the embodiments of the present application can also improve the accuracy and robustness of DBF calculation.

In addition, the embodiment of the present application also simulates the application of DBF calculation in a non-uniform linear array. This simulation still uses the non-uniform linear array shown in FIG. 7, and the set conditions are the same as the simulation conditions in the implementation of the third non-uniform linear array, and will not be repeated.

FIG. 10 exemplarily shows two DBF space spectra, where the first DBF space spectrum is the DBF space spectrum obtained by the embodiment of the present application, and the second DBF space spectrum is the DBF space spectrum obtained by traditional DBF calculation. In the two DBF spatial spectra shown in Fig. 10, the abscissa represents the angle θ with a unit of degree (°), and the ordinate represents the signal strength with a unit of (dB). As shown in Figure 10, the traditional DBF calculation almost fails, and the main lobes and side lobes are almost indistinguishable in the DBF space spectrum. However, by using the embodiment of the present application for DBF calculation, a relatively obvious main lobe can still be obtained. It can be seen that the embodiment of the present application can also improve the accuracy and robustness of the DBF calculation in a non-uniform linear array.

The embodiments of the present application are described above through the method embodiments. Based on the same technical concept, an embodiment of the present application also provides a device. The device may be the frequency analysis device 103 in FIG. 1 or a program instruction installed in the frequency analysis device 103. As shown in FIG. 11, the device 1100 mainly includes an expansion unit 1101 and a calculation unit 1102. The device 1100 can be used to implement any frequency analysis method provided in the foregoing embodiments.

Exemplarily, the expansion unit 1101 is configured to construct an expansion vector r including N vector elements. In the expansion vector r, N vector elements correspond to N flow type parameters, wherein each vector element is used to indicate at least The cross-covariance of a pair of receivers, the flow type parameter corresponding to each vector element is used to indicate that in at least a pair of receivers corresponding to each vector element, the first receiver in each pair of receivers is relative to the second receiver. Orderly distance

The calculation unit 1102 is configured to perform frequency analysis and calculation on the expansion vector r according to the above-mentioned N flow pattern parameters.

In a possible implementation manner, the extension unit 1101 is specifically configured to:

Determine at least one pair of receivers corresponding to each vector element according to the flow parameter corresponding to each vector element;

Obtain the cross-covariance of each pair of receivers in at least one pair of receivers corresponding to each vector element;

For each vector element, calculate the value of each vector element according to the mean value of the cross-covariance of each pair of receivers in at least one pair of receivers;

According to the value of each vector element in the N vector elements, an extended vector r is constructed.

For each vector element, obtain the cross-covariance of any pair of receivers in at least one pair of receivers corresponding to each vector element as the value of each vector element;

Construct a covariance matrix based on the signals received by M receivers. The dimension of the covariance matrix is M×M. The matrix element in the mth row and nth column of the covariance matrix is used to indicate the mth receiver and the nth receiver The cross-covariance between the devices, m and n are both integers in [1,M];

Determine at least one matrix element corresponding to each flow parameter in the covariance matrix;

According to at least one matrix element corresponding to each flow type parameter and each vector element corresponding to each flow type parameter, the mutual covariance of each pair of receivers in at least a pair of receivers corresponding to each vector element is determined.

In a possible implementation manner, the distance between any two adjacent receivers in the M receivers is an integer multiple of the unit distance;

The flow parameter corresponding to each vector element is the difference between the position coordinates of the first receiver in each pair of receivers minus the position coordinates of the second receiver in at least a pair of receivers corresponding to each vector element, Wherein, the position coordinates of the first receiver and the position coordinates of the second receiver are both obtained according to the unit distance.

In a possible implementation manner, the calculation unit 1102 is specifically configured to:

According to the size order of the above N flow pattern parameters, sequentially arrange the N vector elements corresponding to the N flow pattern parameters to obtain the reordered expansion vector

Reordered expansion vector

Perform Fourier transform FFT calculation to obtain FFT spatial spectrum.

According to the order of the size of the N flow type parameters, sequentially arrange the N vector elements corresponding to the N flow type parameters to obtain the reordered expansion vector

, The vector elements corresponding to the two adjacent flow parameters include P-1 interpolation;

Reordered expansion vector

Perform Fast Fourier Transform FFT calculation to obtain FFT spatial spectrum.

Perform digital beamforming DBF calculation on the expansion vector r, and the DBF calculation satisfies the following formula:

Among them, f _DBF (θ) is the DBF space spectrum,

In a possible implementation manner, the N flow type parameters are determined according to the set elements in the difference co-array of the receiving array.

Refer to FIG. 12, which is a schematic diagram of a device provided in this application. The device may be the frequency analysis device 103 in the above-mentioned embodiment. As shown in FIG. 12, the apparatus 1200 includes: a processor 1201 and a memory 1202. Optionally, the apparatus 1200 may further include a bus 1204. Among them, the processor 1201 and the memory 1202 may be connected to each other through a bus 1104; the bus 1204 may be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. . The bus 1204 can be divided into an address bus, a data bus, a control bus, and the like. For ease of representation, only one thick line is used in FIG. 12 to represent it, but it does not mean that there is only one bus or one type of bus.

The processor 1201 may be a CPU, a microprocessor, an ASIC, or one or more integrated circuits used to control the execution of the program of the present application.

The memory 1202 may be a read-only memory (ROM) or other types of static storage devices that can store static information and instructions, random access memory (RAM), or other types that can store information and instructions The dynamic storage device can also be electrically erasable programmable read-only memory (electrically programmable read-only memory, EEPROM), compact disc read-only memory (CD-ROM) or other optical disk storage, Optical disc storage (including compressed optical discs, laser discs, optical discs, digital versatile discs, Blu-ray discs, etc.), magnetic disk storage media or other magnetic storage devices, or can be used to carry or store desired program codes in the form of instructions or data structures and can Any other medium accessed by the computer, but not limited to this. The memory can exist independently and is connected to the processor through the communication line 1204. The memory can also be integrated with the processor.

The memory 1202 is used to store computer-executable instructions for executing the solution of the present application, and the processor 1201 controls the execution. The processor 1201 is configured to execute computer-executable instructions stored in the memory 1202, so as to implement the frequency analysis method provided in the foregoing embodiment of the present application.

Optionally, the computer-executable instructions in the embodiments of the present application may also be referred to as application program codes, which are not specifically limited in the embodiments of the present application.

Those skilled in the art should understand that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, this application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, this application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

This application is described with reference to flowcharts and/or block diagrams of methods, equipment (systems), and computer program products according to this application. It should be understood that each process and/or block in the flowchart and/or block diagram, and the combination of processes and/or blocks in the flowchart and/or block diagram can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing equipment to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing equipment are generated It is a device that realizes the functions specified in one process or multiple processes in the flowchart and/or one block or multiple blocks in the block diagram.

These computer program instructions can also be stored in a computer-readable memory that can guide a computer or other programmable data processing equipment to work in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture including the instruction device. The device implements the functions specified in one process or multiple processes in the flowchart and/or one block or multiple blocks in the block diagram.

These computer program instructions can also be loaded on a computer or other programmable data processing equipment, so that a series of operation steps are executed on the computer or other programmable equipment to produce computer-implemented processing, so as to execute on the computer or other programmable equipment. The instructions provide steps for implementing the functions specified in one process or multiple processes in the flowchart and/or one block or multiple blocks in the block diagram.

Claims

A frequency analysis method, characterized in that it is used to analyze signals received by M receivers, the M receivers are arranged linearly, and M is an integer greater than 1, and the method includes:

Construct an extended vector r including N vector elements, the N vector elements corresponding to N flow type parameters, wherein each of the vector elements is used to indicate the cross-covariance of at least a pair of receivers, and each of the vector elements is used to indicate the cross-covariance of at least a pair of receivers. The flow parameter corresponding to the vector element is used to indicate the orderly distance of the first receiver relative to the second receiver in each pair of receivers in the at least one pair of receivers corresponding to each vector element;

According to the N flow pattern parameters, frequency analysis calculation is performed on the expansion vector r.
The method according to claim 1, wherein constructing an extended vector r including N vector elements includes:

Determine at least a pair of receivers corresponding to each vector element according to the flow type parameter corresponding to each vector element;

Obtaining the cross-covariance of each pair of receivers in the at least one pair of receivers corresponding to each vector element;

For each vector element, calculating the value of each vector element according to the mean value of the cross-covariance of each pair of receivers in the at least one pair of receivers;

The expansion vector r is constructed according to the value of each vector element in the N vector elements.
The method according to claim 1, wherein constructing an extended vector r including N vector elements includes:

Determine at least a pair of receivers corresponding to each vector element according to the flow type parameter corresponding to each vector element;

For each vector element, obtain the cross-covariance of any pair of receivers in at least a pair of receivers corresponding to each vector element, as the value of each vector element;

The expansion vector r is constructed according to the value of each vector element in the N vector elements.
The method according to claim 2, wherein obtaining the cross-covariance of each pair of receivers in the at least one pair of receivers corresponding to each vector element comprises:

Construct a covariance matrix according to the signals received by the M receivers, the dimension of the covariance matrix is M×M, and the matrix element in the mth row and nth column of the covariance matrix is used to indicate the mth receiver The cross-covariance between the receiver and the n-th receiver, m and n are both integers in [1,M];

Determine at least one matrix element corresponding to each flow pattern parameter in the covariance matrix;

According to the at least one matrix element corresponding to each flow type parameter and each vector element corresponding to each flow type parameter, it is determined that in the at least one pair of receivers corresponding to each vector element, each pair receives The cross-covariance of the detector.
The method according to claim 4, wherein the covariance matrix satisfies the following formula:

Wherein, R is the covariance matrix, and x(t) is a reception vector composed of sampling data of the signals received by the M receivers at the t-th sampling point.
The method according to any one of claims 1 to 5, wherein among the M receivers, the cross-covariance between the m-th receiver and the n-th receiver satisfies the following formula:

Among them, x m (t) is the sampling data of the signal received by the m-th receiver at the t-th sampling point, and x n (t) is the signal received by the n-th receiver at the t-th sampling point The sampling data of, m and n are both integers in [1,M], T is the number of sampling points, and T is an integer greater than or equal to 1.
The method according to any one of claims 1 to 6, wherein N is greater than or equal to M, and N is less than M 2 -M+1; or, N is greater than M, and N is less than or equal to M 2 -M +1.
The method according to any one of claims 1 to 7, wherein the distance between any two adjacent receivers in the M receivers is an integer multiple of a unit distance;

The flow parameter corresponding to each vector element is the difference between the position coordinates of the first receiver in each pair of receivers minus the position coordinates of the second receiver in at least a pair of receivers corresponding to each vector element Value, the position coordinates of the first receiver and the position coordinates of the second receiver are all obtained according to the unit distance.
The method according to any one of claims 1 to 8, wherein performing frequency analysis and calculation on the expansion vector r according to the N flow pattern parameters includes:

According to the size order of the N flow type parameters, sequentially arrange the N vector elements corresponding to the N flow type parameters to obtain the reordered expansion vector

The expansion vector of the rearranged order
Perform Fourier transform FFT calculation to obtain FFT spatial spectrum.
The method according to claim 8, wherein performing frequency analysis and calculation on the expansion vector r according to the N flow pattern parameters comprises:

According to the size order of the N flow type parameters, sequentially arrange the N vector elements corresponding to the N flow type parameters to obtain the reordered expansion vector

If among the N flow pattern parameters arranged in sequence, the difference between two adjacent flow pattern parameters is P, and P is an integer greater than 1, then the sequence rearranged expansion vector is obtained
Wherein, the vector elements corresponding to the two adjacent flow pattern parameters respectively include P-1 interpolation values;

The expansion vector of the rearranged order
Perform Fast Fourier Transform FFT calculation to obtain FFT spatial spectrum.
The method according to any one of claims 1 to 10, wherein performing frequency analysis and calculation on the expansion vector r according to the N flow pattern parameters includes:

Perform digital beamforming DBF calculation on the expansion vector r, and the DBF calculation satisfies the following formula:

Among them, f DBF (θ) is the DBF space spectrum,
Is a steering vector constructed according to the expansion vector r and the N flow pattern parameters, θ∈Θ, Θ is a set of discrete search intervals.
The method according to any one of claims 1 to 11, wherein the N flow type parameters are determined according to set elements in a set difference co-array of the receiving array.
A device, characterized in that it is used to analyze signals received by M receivers, the M receivers are arranged linearly, and M is an integer greater than 1, the device includes an expansion unit and a calculation unit, wherein:

The extension unit is configured to construct an extension vector r including N vector elements, the N vector elements corresponding to N flow type parameters, and each of the vector elements is used to indicate the interaction of at least a pair of receivers. Covariance, the flow type parameter corresponding to each vector element is used to indicate that in the at least one pair of receivers corresponding to each vector element, the difference between the first receiver and the second receiver in each pair of receivers Orderly distance

The calculation unit is configured to perform frequency analysis and calculation on the expansion vector r according to the N flow pattern parameters.
The device according to claim 13, wherein the extension unit is specifically configured to:

Determine at least a pair of receivers corresponding to each vector element according to the flow type parameter corresponding to each vector element;

Obtaining the cross-covariance of each pair of receivers in the at least one pair of receivers corresponding to each vector element;

For each vector element, calculating the value of each vector element according to the mean value of the cross-covariance of each pair of receivers in the at least one pair of receivers;

The expansion vector r is constructed according to the value of each vector element in the N vector elements.
The device according to claim 13, wherein the extension unit is specifically configured to:

Determine at least a pair of receivers corresponding to each vector element according to the flow type parameter corresponding to each vector element;

For each vector element, obtain the cross-covariance of any pair of receivers in at least one pair of receivers corresponding to each vector element, as the value of each vector element;

The expansion vector r is constructed according to the value of each vector element in the N vector elements.
The device according to claim 14, wherein the extension unit is specifically configured to:

Construct a covariance matrix according to the signals received by the M receivers, the dimension of the covariance matrix is M×M, and the matrix element in the mth row and nth column of the covariance matrix is used to indicate the mth receiver The cross-covariance between the receiver and the n-th receiver, m and n are both integers in [1,M];

Determine at least one matrix element corresponding to each flow pattern parameter in the covariance matrix;

According to the at least one matrix element corresponding to each flow type parameter and each vector element corresponding to each flow type parameter, it is determined that in the at least one pair of receivers corresponding to each vector element, each pair receives The cross-covariance of the detector.
The device according to claim 16, wherein the covariance matrix satisfies the following formula:

Wherein, R is the covariance matrix, and x(t) is a reception vector composed of sampling data at the t-th sampling point of the signals received by the M receivers.
The apparatus according to any one of claims 13 to 17, wherein in the M receivers, the cross-covariance between the m-th receiver and the n-th receiver satisfies the following formula:

Among them, x m (t) is the sampling data of the signal received by the m-th receiver at the t-th sampling point, and x n (t) is the signal received by the n-th receiver at the t-th sampling point The sampling data of, m and n are both integers in [1,M], T is the number of sampling points, and T is an integer greater than or equal to 1.
The device according to any one of claims 13 to 18, wherein N is greater than or equal to M, and N is less than M 2 -M+1; or, N is greater than M, and N is less than or equal to M 2 -M +1.
The device according to any one of claims 13 to 19, wherein the distance between any two adjacent receivers in the M receivers is an integer multiple of a unit distance;

The flow parameter corresponding to each vector element is the difference between the position coordinates of the first receiver in each pair of receivers minus the position coordinates of the second receiver in at least a pair of receivers corresponding to each vector element Value, the position coordinates of the first receiver and the position coordinates of the second receiver are all obtained according to the unit distance.
The device according to any one of claims 13 to 20, wherein the calculation unit is specifically configured to:

According to the size order of the N flow type parameters, sequentially arrange the N vector elements corresponding to the N flow type parameters to obtain the reordered expansion vector

The expansion vector of the rearranged order
Perform Fourier transform FFT calculation to obtain FFT spatial spectrum.
The device according to claim 20, wherein the calculation unit is specifically configured to:

According to the size order of the N flow type parameters, sequentially arrange the N vector elements corresponding to the N flow type parameters to obtain the reordered expansion vector

If among the N flow pattern parameters arranged in sequence, the difference between two adjacent flow pattern parameters is P, and P is an integer greater than 1, then the sequence rearranged expansion vector is obtained
Wherein, the vector elements corresponding to the two adjacent flow pattern parameters respectively include P-1 interpolation values;

The expansion vector of the rearranged order
Perform Fast Fourier Transform FFT calculation to obtain FFT spatial spectrum.
The device according to any one of claims 13 to 22, wherein the calculation unit is specifically configured to:

Perform digital beamforming DBF calculation on the expansion vector r, and the DBF calculation satisfies the following formula:

Among them, f DBF (θ) is the DBF space spectrum,
Is a steering vector constructed according to the expansion vector r and the N flow pattern parameters, θ∈Θ, Θ is a set of discrete search intervals.
The apparatus according to any one of claims 13 to 23, wherein the N flow type parameters are determined according to set elements in a set difference co-array of the receiving array.
A device, characterized in that the device includes a processor and a memory;

The memory is used to store computer programs or instructions;

The processor is configured to execute a computer program or instruction stored in the memory, so that the device executes the frequency analysis method according to any one of claims 1 to 12.
A computer-readable storage medium, characterized in that, a computer program or instruction is stored in the computer-readable storage medium, and when the computer reads and executes the computer program or instruction, the computer executes claims 1 to 12 The frequency analysis method described in any one of.
A radar, characterized by comprising a transmitter, a receiving array and a frequency analysis device, the receiving array comprising M linearly arranged receivers, where M is an integer greater than 1;

The transmitter is used to transmit a detection signal;

The receiving array is used to receive echo signals;

The frequency analysis device is configured to perform frequency analysis on the received signal of the receiving array according to the frequency analysis method provided in any one of claims 1 to 12, and the received signal of the receiving array includes the echo signal.